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博碩士論文 etd-1129120-165624 詳細資訊
Title page for etd-1129120-165624
論文名稱
Title
在竊聽者存在下的安全且節能的無線感測器網路分佈式檢測
Secure and Energy-Efficient Distributed Detection Wireless Sensor Network for IoT in the Presence of an Eavesdropper
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
52
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2020-12-29
繳交日期
Date of Submission
2020-12-29
關鍵字
Keywords
IoT、信息審查、瑞利衰落通道選擇和加密、竊聽者、完美保密、無線感測網路、分散式偵測
IoT, Information censoring, Rayleigh fading channel selection and encryption, eavesdropper, perfect secrecy, Wireless sensor network, Distributed detection
統計
Statistics
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中文摘要
無線傳感器網絡(Wireless Sensor Network)一直被認為是其廣泛應用的關鍵技術之一,例如跨不同區域的檢測,監視和監視。 利用WSN的一個特定創新領域是物聯網(Internet of Things)。

本文考慮了分佈式檢測WSN,其中推理網絡在無源竊聽者的存在下運行。 提供了一種涉及審查方案的物理層方法來解決能源效率問題,並且為了網絡安全性使用了位翻轉加密。 在融合中心將最佳和次優決策融合作為可行的規則進行比較,並使用蒙特卡洛模擬進行各自的錯誤概率表現。 使用Kullback-Leibler散度(KLD)作為安全性度量,可以觀察到完美保密方案。

這項研究還研究了網絡加密組大小對稱性與安全性的關鍵作用。 如果翻轉和非翻轉組的大小由於初始信息審查而有所不同,則會出現漸近完美保密方案。 為了補償不均勻的組大小的影響,我們要么更改傳感器的激活數量和總數,要么在另一個之上引入另一個檢查,通道選擇。 結果表明,雙重審查策略在能效和數據保密性方面佔優勢。
Abstract
Wireless sensor network (WSN) has always been regarded as one of the key technologies in terms of its extensive application such as detection, surveillance, and monitoring across different areas. One particular innovative field that utilizes WSN is the Internet of Things (IoT).

This thesis considers a distributed detection in WSN where inference network operates in the presence of a passive eavesdropper. A physical-layer approach involving censoring scheme is provided to address energy efficiency and a bit-flipping encryption is in place for network security. Optimal and sub-optimal decision fusion are compared as viable rule in the fusion center and their respective error probability performances are conducted using Monte-carlo simulation. Perfect Secrecy scenario is observed using Kullback-Leibler divergence (KLD) as the security metric.

This research investigates as well the crucial effect of network encrypted group size symmetry versus security. In the event flipping and non-flipping groups differ in size due to initial information censoring, asymptotic perfect secrecy scenario occurs. In order to compensate the effect of uneven group sizes, we either vary the activated and total number of sensors or introduce another censoring, channel selection, on top of the other. Results show that the double censoring strategy prevails in terms of energy saving and data confidentiality.
目次 Table of Contents
Thesis Validation Letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .i
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
Chapter 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Research Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2
1.3 Thesis Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Chapter 2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
2.1 Wireless Sensor Network Literature . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Physical Layer Censoring Techniques in WSN . . . . . . . . . . . . . . . . .7
2.3 Security Attacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.1 Passive attacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8
2.3.2 Active attacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Chapter 3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9
3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 Distributed Detection with Home FC . . . . . . . . . . . . . . . . . . . . . . . .10
3.2.1 Local Detection in Sensor Node . . . . . . . . . . . . . . . . . . . . . . . . . .10
3.2.2 Information Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.2.2.1 Information Selection Threshold . . . . . . . . . . . . . . . . . . . . . . . .14
3.2.3 Transmission of Local Decisions from Sensors to HFC . . . . . . 16
3.2.4 Decision Fusion in the Home FC . . . . . . . . . . . . . . . . . . . . . . . . . .16
3.2.4.1 Optimal LR-Based Fusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17
3.2.4.2 Maximum Ratio Combining Fusion (Sub-optimal) . . . . . . . . . .17
3.2.5 Error Probability Derivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18
3.3 Distributed Detection with Home and Neighbor FC . . . . . . . . . . . . 19
3.3.1 Encryption Scheme. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
3.3.2 Perfect Secrecy Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20
3.3.3 Asymptotic Perfect Secrecy Condition . . . . . . . . . . . . . . . . . . . . . 22
3.3.4 Channel Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.4 Kullback-Leibler Divergence (KLD) Derivation . . . . . . . . . . . . . . . . . 23
3.4.1 KLD in HFC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23
3.4.2 KLD in NBFC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.4.3 Overall KLD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Chapter 4 Simulation Results and Discussion . . . . . . . . . . . . . . . . . . . . 27
4.1 Error Probability vs. Activated Sensors Rate . . . . . . . . . . . . . . . . . . 27
4.2 Error Probability vs. SNR - Perfect Secrecy . . . . . . . . . . . . . . . . . . . .28
4.3 Error Probability vs. SNR - Asymptotic Perfect Secrecy. . . . . . . . . .29
4.4 KLD vs. Flipping probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.5 KLD vs. Activated and Total Number of Sensors . . . . . . . . . . . . . . .32
4.6 Error Probability of HFC and NBFC with Double Censoring . . . . . . 33
Chapter 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35
Appendix. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36
Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
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